Efficient and Reliable Federated Recommendation System in Temporal Scenarios

Author:

Ye Jingzhou,Lin Hui,Wang Xiaoding,Dong Chen,Liu Jianmin

Publisher

Springer Nature Singapore

Reference14 articles.

1. Zhao, Z.-D., Shang, M.-S.: User-based collaborative-filtering recommendation algorithms on Hadoop. In: 2010 Third International Conference on Knowledge Discovery and Data Mining, pp. 478–481. IEEE (2010)

2. Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International Conference on World Wide Web, pp. 285–295 (2001)

3. Goddard, M.: The EU general data protection regulation (GDPR): European regulation that has a global impact. Int. J. Mark. Res. 59(6), 703–705 (2017)

4. McMahan, B., Moore, E., Ramage, D., Hampson, S., y Arcas, B.A.: Communication-efficient learning of deep networks from decentralized data. In: Artificial Intelligence and Statistics, pp. 1273–1282. PMLR (2017)

5. Ammad-Ud-Din, M., et al.: Federated collaborative filtering for privacy-preserving personalized recommendation system (2019). arXiv preprint arXiv:1901.09888

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